1. Field of the Invention
The present invention relates to enhancing the accuracy of point of origin estimates, and, more specifically, to a method of using a Kalman filter cascade to improve point of origin accuracy.
2. Description of the Related Art
A mortar is a projectile that launches explosive shells in high trajectories to penetrate enemy defenses and inflict both damage and casualties. Mortar shells can be launched from light-weight portable weapons and can be efficiently moved from location to location to avoid counterattack.
Quickly and accurately determining the point of origin of an in-flight projectile such as a mortar has the potential to greatly enhance defensive capabilities. With an accurate point of origin estimation, a counterattack can commence before the enemy can move the weapon.
Radar is typically used to detect and track in-flight projectiles. The United States AN/TPQ-48 lightweight counter-mortar radar, for example, is a 360-degree radar used to detect, locate, and report enemy indirect fire. Optimally, the counter-mortar radar is designed to determine both point of origin and weapon type and subtype within seconds, allowing rapid and effective countermeasures.
All counter-fire radars employ some type of algorithm to determine projectile point of origin. Predecessors to the AN/TPQ-48 counter-mortar radar, for example, typically use a Kalman filter-based weapon state estimation routine that takes into account ballistic flight characteristics. A Kalman filter is an optimal data processing algorithm used to obtain the best estimate of a variable using noisy measurements. By combining measurements with information about the sensor and about the overall system, the algorithm returns an estimate with minimized error.
Despite the use of algorithms such as the Kalman filter, current point of origin estimates remain error-prone and inaccurate. An improved algorithm is needed to increase the accuracy of point of origin estimates to support counter-attack capabilities.